1. Field of the Invention
This invention relates to a blood pressure measurement apparatus and method in which a waveform discrimination method is used in the recognition of Korotkoff sounds in the measurement of blood pressure by auscultation.
2. Description of the Prior Art
In the detection of Korotkoff sounds according to the prior art, the most widespread approach is a discrimination method using a filter and comparator. This is referred to as the filter comparator method. Another approach used much less widely is a discrimination method, namely a pattern recognition method, which is based on the waveform of the Korotkoff sounds.
It is known that the spectral distribution of Korotkoff sounds generally has a frequency component different from body movement and external noise. The filter comparator method utilizes this fact and measures blood pressure by filtering a signal detected by a microphone attached to a pressure cuff fastened to a patient's arm, reducing the amplitude of frequency components other than the frequency component of the Korotkoff sounds, then comparing the frequency component of the Korotkoff sounds with a preset threshold value by means of a voltage comparator, and discriminating this frequency component based on its magnitude.
However, the frequency component of Korotkoff sounds not only varies from one patient to another but also differs for one and the same patient depending upon such measurement conditions as the time at which measurement is made and cuff pressure Moreover, since the frequency band of interest is fairly wide, ranging from several tens of Hertz to 200-300 Hz, it is very difficult to extract solely the Korotkoff sound component by removing the sound of the patient's pulse and noise.
When the frequency component of the Korotkoff sounds is small in comparison with the sound of the patient's pulse, it is difficult to distinguish between the pulse sound and the Korotkoff sounds. Furthermore, since the discrimination is made based on a voltage level, measurement precision is readily influenced by any disparity in the amplitude of the Korotkoff sounds.
The aforementioned pattern recognition method in which discrimination is made based on the waveform of the Korotkoff sounds has recently been put into partial practical use.
In general, the waveform of a Korotkoff sound is as shown in FIG. 2(A). The waveform is subjected to an A-D conversion so as to make it easier to process the sound data detected by a pick up, with the digital signal resulting from the conversion being stored in means such as a memory. This is referred to as pattern detection processing. Next, maximum and minimum values are calculated from the stored signal values. For example, characteristic points are successively detected, as shown at C1, C2, C3, C4 in FIG. 3(A), four of such points being the minimum number necessary. This is referred to as a characteristic point plotting step. After the characteristic points have been detected, the general position of each characteristic point is verified and a decision is rendered as to whether the waveform is indeed indicative of a Korotkoff sound. This step is referred to as a discrimination processing step. Thus, recognition processing is divided into three process blocks.
If a characteristic point is not detected in the characteristic point plotting processing step, the pattern detection processing step is returned to for further signal read in. If a decision is rendered in the discrimination step to the effect that the waveform is not that of a Korotkoff sound, processing is executed for detecting further characteristic points or for reading in a new signal.
The relationship among the pattern recognition processing blocks is illustrated in FIG. 6.
A problem encountered in the pattern recognition approach is that in the actual measurement data obtained from a living body, a fine ripple shown in FIG. 7 tends to be produced in the vicinity of the maximum and minimum points of the Korotkoff sound signal owing to the influence an A-D conversion error.
Accordingly, with the method of detecting maximum and minimum values one by one while traversing the signal waveform in regular order and then treating each such value as a characteristic point, there is very large amount of feedback from the discrimination processing and, hence, the method requires a considerable period of time for execution. In addition, there is strong possibility that characteristic points will be detected erroneously.